A robust layer adapted difference method for singularly perturbed two-parameter parabolic problems

A finite difference method for a time-dependent singularly perturbed convection-diffusion-reaction problem involving two small parameters in one space dimension is considered. We use the classical implicit Euler method for time discretization and upwind scheme on the Shishkin-Bakhvalov mesh for spatial discretization. The method is analysed for convergence and is shown to be uniform with respect to both the perturbation parameters. The use of the Shishkin-Bakhvalov mesh gives first-order convergence unlike the Shishkin mesh where convergence is deteriorated due to the presence of a logarithmic factor. Numerical results are presented to validate the theoretical estimates obtained.

Poly(alkylene itaconate)s - an interesting class of polyesters with periodically located exo-chain double bonds susceptible to Michael addition

Itaconic acid is a bio-sourced dicarboxylic acid that carries a double bond; although several reports have dealt with the radical-initiated chain polymerization of dialkyl itaconates, only a few studies have utilized it as a di-acid monomer to prepare polyesters. In this study, we demonstrate that dibutyl itaconate can be melt-condensed with aliphatic diols to generate unsaturated polyesters; importantly, we show that the double bonds remain unaffected during the melt polymerization. A particularly useful attribute of these polyesters is that the exo-chain double bonds are conjugated to the ester carbonyl and, therefore, can serve as excellent Michael acceptors. A variety of organic thiols, such as alkane thiols, MPEG thiol, thioglycerol, derivatized cysteine etc., were shown to quantitatively Michael-add to the exo-chain double bonds and generate interesting functionalized polyesters. Similarly, organic amines, such as N-methyl-benzylamine, diallyl amine and proline, also add across the double bond; thus, these poly(alkylene itaconate)s could serve as potentially bio-benign polyesters that could be quantitatively transformed into a variety of interesting and potentially useful functionalized polymers.

An Easy Access to Benzofurans via DBU Induced Condensation Reaction of Active 2-Hydroxy Acetophenones with Phenacyl Chlorides: A Novel Class of Antioxidant Agents

A convenient and efficient one-pot synthesis of benzofurans 3a, 3b, 3c, 3d, 3e, 3f, 3g, 3h, 3i, 3j, 3k, 3l, 3m, 3n, 3o, 3p, 3q, 3r, 3s, 3t has been described from 2-hydroxy acetophenones and phenacyl chlorides in the presence of DBU. The procedure was applicable for a variety of phenacyl chlorides and provides a variety of benzofurans with higher yields. DBU acts as a base and as well as nucleophiles. All the derivatives were subjected to in vitro antioxidant screenings against representative 2,2-diphenyl-1-picryl-hydrazyl and 2,2-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) radicals and results worth for further investigations.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations

The Lattice-Boltzmann method (LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a state-of-the-art LBM solver such as Palabos, a user has to still manually write the program using library-supplied primitives. We propose an automated code generator for a class of LBM computations with the objective to achieve high performance on modern architectures. Few studies have looked at time tiling for LBM codes. We exploit a key similarity between stencils and LBM to enable polyhedral optimizations and in turn time tiling for LBM. We also characterize the performance of LBM with the Roofline performance model. Experimental results for standard LBM simulations like Lid Driven Cavity, Flow Past Cylinder, and Poiseuille Flow show that our scheme consistently outperforms Palabos-on average by up to 3x while running on 16 cores of an Intel Xeon (Sandybridge). We also obtain an improvement of 2.47x on the SPEC LBM benchmark.

Comparison of a priori and a posteriori meshes for singularly perturbed nonlinear parameterized problems

This paper deals with the adaptive mesh generation for singularly perturbed nonlinear parameterized problems with a comparative research study on them. We propose an a posteriori error estimate for singularly perturbed parameterized problems by moving mesh methods with fixed number of mesh points. The well known a priori meshes are compared with the proposed one. The comparison results show that the proposed numerical method is highly effective for the generation of layer adapted a posteriori meshes. A numerical experiment of the error behavior on different meshes is carried out to highlight the comparison of the approximated solutions. (C) 2015 Elsevier B.V. All rights reserved.

A new class of high strength high temperature Cobalt based gamma-gamma ` Co-Mo-Al alloys stabilized with Ta addition

The present paper reports a new class of Co based superalloys that has gamma-gamma' microstructure and exhibits much lower density compared to other commercially available Co superalloys including Co-Al-W based alloys. The basic composition is Co-10Al-5Mo (at%) with addition of 2 at% Ta for stabilization of gamma' phase. The gamma-gamma' microstructure evolves through solutionising and aging treatment. Using first principles calculations, we observe that Ta plays a crucial role in stabilizing gamma' phase. By addition of Ta in the basic stoichiometric composition Co-3(Al, Mo), the enthalpy of formation (Delta H-f) of L1(2) structure (gamma' phase) becomes more negative in comparison to DO19 structure. The All of the L12 structure becomes further more negative by the occupancy of Ni and Ti atoms in the lattice suggesting an increase in the stability of the gamma' precipitates. Among large number of alloys studied experimentally, the paper presents results of detailed investigations on Co-10Al-5Mo-2Ta, Co-30Ni-10Al-5Mo-2Ta and Co-30Ni-10Al-5Mo-2Ta-2Ti. To evaluate the role alloying elements, atom probe tomography investigations were carried out to obtain partition coefficients for the constituent elements. The results show strong partitioning of Ni, Al, Ta and Ti in ordered gamma' precipitates. 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Minimization Problems Based on Relative alpha-Entropy I: Forward Projection

Minimization problems with respect to a one-parameter family of generalized relative entropies are studied. These relative entropies, which we term relative alpha-entropies (denoted I-alpha), arise as redundancies under mismatched compression when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative entropies are a generalization of the usual relative entropy (Kullback-Leibler divergence). Just like relative entropy, these relative alpha-entropies behave like squared Euclidean distance and satisfy the Pythagorean property. Minimizers of these relative alpha-entropies on closed and convex sets are shown to exist. Such minimizations generalize the maximum Renyi or Tsallis entropy principle. The minimizing probability distribution (termed forward I-alpha-projection) for a linear family is shown to obey a power-law. Other results in connection with statistical inference, namely subspace transitivity and iterated projections, are also established. In a companion paper, a related minimization problem of interest in robust statistics that leads to a reverse I-alpha-projection is studied.

Lower-Bound Axisymmetric Formulation for Geomechanics Problems Using Nonlinear Optimization

A lower-bound limit analysis formulation, by using two-dimensional finite elements, the three-dimensional Mohr-Coulomb yield criterion, and nonlinear optimization, has been given to deal with an axisymmetric geomechanics stability problem. The optimization was performed using an interior point method based on the logarithmic barrier function. The yield surface was smoothened (1) by removing the tip singularity at the apex of the pyramid in the meridian plane and (2) by eliminating the stress discontinuities at the corners of the yield hexagon in the pi-plane. The circumferential stress (sigma(theta)) need not be assumed. With the proposed methodology, for a circular footing, the bearing-capacity factors N-c, N-q, and N-gamma for different values of phi have been computed. For phi = 0, the variation of N-c with changes in the factor m, which accounts for a linear increase of cohesion with depth, has been evaluated. Failure patterns for a few cases have also been drawn. The results from the formulation provide a good match with the solutions available from the literature. (C) 2014 American Society of Civil Engineers.

Unique Covering Problems with Geometric Sets

The Exact Cover problem takes a universe U of n elements, a family F of m subsets of U and a positive integer k, and decides whether there exists a subfamily(set cover) F' of size at most k such that each element is covered by exactly one set. The Unique Cover problem also takes the same input and decides whether there is a subfamily F' subset of F such that at least k of the elements F' covers are covered uniquely(by exactly one set). Both these problems are known to be NP-complete. In the parameterized setting, when parameterized by k, Exact Cover is W1]-hard. While Unique Cover is FPT under the same parameter, it is known to not admit a polynomial kernel under standard complexity-theoretic assumptions. In this paper, we investigate these two problems under the assumption that every set satisfies a given geometric property Pi. Specifically, we consider the universe to be a set of n points in a real space R-d, d being a positive integer. When d = 2 we consider the problem when. requires all sets to be unit squares or lines. When d > 2, we consider the problem where. requires all sets to be hyperplanes in R-d. These special versions of the problems are also known to be NP-complete. When parameterizing by k, the Unique Cover problem has a polynomial size kernel for all the above geometric versions. The Exact Cover problem turns out to be W1]-hard for squares, but FPT for lines and hyperplanes. Further, we also consider the Unique Set Cover problem, which takes the same input and decides whether there is a set cover which covers at least k elements uniquely. To the best of our knowledge, this is a new problem, and we show that it is NP-complete (even for the case of lines). In fact, the problem turns out to be W1]-hard in the abstract setting, when parameterized by k. However, when we restrict ourselves to the lines and hyperplanes versions, we obtain FPT algorithms.

A FRAMEWORK FOR THE ERROR ANALYSIS OF DISCONTINUOUS FINITE ELEMENT METHODS FOR ELLIPTIC OPTIMAL CONTROL PROBLEMS AND APPLICATIONS TO C-0 IP METHODS

In this article, an abstract framework for the error analysis of discontinuous Galerkin methods for control constrained optimal control problems is developed. The analysis establishes the best approximation result from a priori analysis point of view and delivers a reliable and efficient a posteriori error estimator. The results are applicable to a variety of problems just under the minimal regularity possessed by the well-posedness of the problem. Subsequently, the applications of C-0 interior penalty methods for a boundary control problem as well as a distributed control problem governed by the biharmonic equation subject to simply supported boundary conditions are discussed through the abstract analysis. Numerical experiments illustrate the theoretical findings.

Graph Modification Problems: A Modern Perspective

We give an overview of recent results and techniques in parameterized algorithms for graph modification problems.

DETERMINISTIC ALGORITHMS FOR MATCHING AND PACKING PROBLEMS BASED ON REPRESENTATIVE SETS

In this work, we study the well-known r-DIMENSIONAL k-MATCHING ((r, k)-DM), and r-SET k-PACKING ((r, k)-SP) problems. Given a universe U := U-1 ... U-r and an r-uniform family F subset of U-1 x ... x U-r, the (r, k)-DM problem asks if F admits a collection of k mutually disjoint sets. Given a universe U and an r-uniform family F subset of 2(U), the (r, k)-SP problem asks if F admits a collection of k mutually disjoint sets. We employ techniques based on dynamic programming and representative families. This leads to a deterministic algorithm with running time O(2.851((r-1)k) .vertical bar F vertical bar. n log(2)n . logW) for the weighted version of (r, k)-DM, where W is the maximum weight in the input, and a deterministic algorithm with running time O(2.851((r-0.5501)k).vertical bar F vertical bar.n log(2) n . logW) for the weighted version of (r, k)-SP. Thus, we significantly improve the previous best known deterministic running times for (r, k)-DM and (r, k)-SP and the previous best known running times for their weighted versions. We rely on structural properties of (r, k)-DM and (r, k)-SP to develop algorithms that are faster than those that can be obtained by a standard use of representative sets. Incorporating the principles of iterative expansion, we obtain a better algorithm for (3, k)-DM, running in time O(2.004(3k).vertical bar F vertical bar . n log(2)n). We believe that this algorithm demonstrates an interesting application of representative families in conjunction with more traditional techniques. Furthermore, we present kernels of size O(e(r)r(k-1)(r) logW) for the weighted versions of (r, k)-DM and (r, k)-SP, improving the previous best known kernels of size O(r!r(k-1)(r) logW) for these problems.

First-in-Class Inhibitors of Sulfur Metabolism with Bactericidal Activity against Non-Replicating M-tuberculosis

Development of effective therapies to eradicate persistent, slowly replicating M. tuberculosis (Mtb) represents a significant challenge to controlling the global TB epidemic. To develop such therapies, it is imperative to translate information from metabolome and proteome adaptations of persistent Mtb into the drug discovery screening platforms. To this end, reductive sulfur metabolism is genetically and pharmacologically implicated in survival, pathogenesis, and redox homeostasis of persistent Mtb. Therefore, inhibitors of this pathway are expected to serve as powerful tools in its preclinical and clinical validation as a therapeutic target for eradicating persisters. Here, we establish a first functional HTS platform for identification of APS reductase (APSR) inhibitors, a critical enzyme in the assimilation of sulfate for the biosynthesis of cysteine and other essential sulfur-containing molecules. Our HTS campaign involving 38?350 compounds led to the discovery of three distinct structural classes of APSR inhibitors. A class of bioactive compounds with known pharmacology displayed potent bactericidal activity in wild-type Mtb as well as MDR and XDR clinical isolates. Top compounds showed markedly diminished potency in a conditional Delta APSR mutant, which could be restored by complementation with Mtb APSR. Furthermore, ITC studies on representative compounds provided evidence for direct engagement of the APSR target. Finally, potent APSR inhibitors significantly decreased the cellular levels of key reduced sulfur-containing metabolites and also induced an oxidative shift in mycothiol redox potential of live Mtb, thus providing functional validation of our screening data. In summary, we have identified first-in-class inhibitors of APSR that can serve as molecular probes in unraveling the links between Mtb persistence, antibiotic tolerance, and sulfate assimilation, in addition to their potential therapeutic value.